Project Summary/Abstract Every year, approximately 1,200 severe mistreatments happen in radiation therapy. Radiation therapy lawsuits rank in the top third of all medical specialties with an average of $313,000 per claim settled or litigated. The current method for detecting treatment errors is by a weekly patient chart check, where each treatment record is manually reviewed on a weekly basis. This labor-intensive and inefficient method prevents us from detecting the treatment error at an early stage. Here we propose a novel software system, ChartAlert, for automating patient chart checking. ChartAlert is a prospective real-time adaptive electronic checking system that can be configured to support different clinical workflows and perform ?smart? check using artificial intelligence. It supports two major treatment databases (Elekta MOSAIQ and Varian ARIA) in radiotherapy. In Phase I project, we have successfully developed ChartAlert for MOSAIQ prototype that is under clinical testing in two treatment centers. Our preliminary results demonstrated the significant improvement of effectiveness in patient chart checking and the flexibility of supporting different workflows. In this Phase II proposal, we will continue the ChartAlert development. We will demonstrate the feasibility of the ChartAlert approach and its advantages over the standard manual checking method. We will develop a prospective checking module, develop the ARIA data translation module for ChartAlert for ARIA, design and implement an AI-based ?smart? check module, and verify the proposed system at the partner sites. Successful completion of these aims will demonstrate the feasibility and commercial potential of the ChartAlert approach. Ultimately, this work will result in an intelligent patient chart checking software, which will increase patient chart check efficiency, save staff time, improve cancer patient treatment safety, and preventing potential lawsuits.